Stars
Official implementation of "S²M²: Scalable Stereo Matching Model for Reliable Depth Estimation, ICCV 2025"
View a Git Graph of your repository in Visual Studio Code, and easily perform Git actions from the graph.
Automated TDD enforcement for Claude Code
[CVPR 2025] DEFOM-Stereo: Depth foundation model based stereo matching
[CVPR 2025 Best Paper Nomination] FoundationStereo: Zero-Shot Stereo Matching
An extremely fast Python package and project manager, written in Rust.
Productive, portable, and performant GPU programming in Python.
CUDA accelerated rasterization of gaussian splatting
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Eglcr: Edge Structure Guidance and Scale Adaptive Attention for Iterative Stereo Matching(ACM MM24)
[TPAMI 2025 & CVPR 2023] Iterative Geometry Encoding Volume for Stereo Matching
Non-official Pytorch implementation of the CREStereo(CVPR 2022 Oral).
An extremely fast Python linter and code formatter, written in Rust.
[CVPR 2024 Highlight] Selective-Stereo: Adaptive Frequency Information Selection for Stereo Matching
An evaluation framework for machine learning models simulating high-throughput materials discovery.
Naive Svelte Masonry component without column balancing (ragged columns at the bottom)
Sticky responsive table of contents component
Interactive browser visualizations for materials science: periodic tables, 3d crystal structures, MD trajectories, heatmaps, scatter plots, histograms.
A toolkit for visualizations in materials informatics.
Accompanying library for the Record3D iOS app (https://record3d.app/). Allows you to receive RGBD stream from iOS devices with TrueDepth camera(s).
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8…
Using ARKit and LiDAR to save depth data and export point cloud, based on WWDC20-10611 sample code
Running large language models on a single GPU for throughput-oriented scenarios.
A latent text-to-image diffusion model
Convert Machine Learning Code Between Frameworks